AI-Native Forward Deployed Engineer

Build and deploy AI-native applications, agentic workflows, RAG pipelines, and multi-agent systems. Develop MCP integrations, tool-use workflows, evaluations, and AI observability solutions. Use AI coding tools such as Claude Code, Cursor, GitHub Copilot, or equivalent. Partner with engineering leadership to develop and execute AI adoption roadmaps. Establish best practices for AI-assisted development, testing, security, and governance. Mentor engineers and help teams adopt AI-native development across the organization. Prototype rapidly and productionize solutions using strong CI/CD, cloud, and engineering practices. Travel to customer sites as required.

8+ years of production software engineering experience. Strong experience with Python, TypeScript, C#, Java, or Node.js. Hands-on experience with LLMs, RAG, prompting/context engineering, tool use, evaluation, and observability. Experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK. Experience with AWS, Azure, or Google Cloud Platform, Docker, Kubernetes, and CI/CD. Strong customer-facing consulting, communication, and technical leadership skills. Preferred: Experience building MCP servers/integrations. Forward-deployed engineering, professional services, or enterprise consulting experience. Experience leading AI adoption, Developer Experience (DevEx), or platform transformation. Knowledge of AI security, IP/licensing, data residency, and model governance.